Sightseeing plan recommendation system using sequential pattern mining based on adjacent activities

This study proposes the novel sightseeing plan recommendation system based on the ad jacency of the activities in the plans (e.g., a shopping is selected after a lunch), and aims at verifying its effectiveness through the subject experiments. The proposed system recommends the sightseeing plans according to the adjacent relationship of the activities in the plans given by the group of other users whose preference are similar to the user. The intensive subject experiments have revealed that our proposed system can recommend the plans that contains the appropriate order of activities for the sightseeing plan recommendation in comparison with ones recommended by the conventional system.